Triple

T2962895
Position Surface form Disambiguated ID Type / Status
Subject Indra Nooyi E80088 entity
Predicate employer P7 FINISHED
Object PepsiCo E136151 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: PepsiCo | Statement: [Indra Nooyi, employer, PepsiCo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PepsiCo
Context triple: [Indra Nooyi, employer, PepsiCo]
  • A. PepsiCo chosen
    PepsiCo is a multinational food, snack, and beverage corporation best known for producing the Pepsi soft drink and a wide portfolio of global consumer brands.
  • B. The Coca-Cola Company
    The Coca-Cola Company is a multinational beverage corporation best known as the producer of the iconic soft drink Coca-Cola and a wide portfolio of nonalcoholic beverages sold worldwide.
  • C. Coca-Cola
    Coca-Cola is a globally recognized carbonated soft drink, known for its distinctive cola flavor and iconic red-and-white branding.
  • D. Pepsi
    Pepsi is a globally recognized carbonated soft drink brand produced by PepsiCo and known as one of the main competitors to Coca-Cola.
  • E. Coca-Cola FEMSA
    Coca-Cola FEMSA is the largest franchise bottler of Coca-Cola products in the world, operating extensive beverage production and distribution networks across Latin America and parts of Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9957602c819089b673966fd619e0 completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc959b3c8190a0d95a3e616246f9 completed March 11, 2026, 5:24 a.m.
Created at: March 8, 2026, 2:57 p.m.